For capturing or identifying motor vehicles in flowing traffic, numerous methods are known. In addition, there exists a broad spectrum of sensor options, with which motor vehicles can be recognized on the basis of various features. A broad field in this respect is here the identification using external features. In a special form, such features are ascertained from motor-vehicle contours. These are obtained from profile recordings of light barrier systems or from images from video or photo systems placed above the road. It is thus possible by evaluating features of the vehicle front or of other suitable views of motor vehicles to distinguish between vehicles.
Frequently, image-based identification systems are also combined with license plate recognition, in which the registration number of the motor vehicle is ascertained from an image of the front or rear view using optical character recognition (OCR). Systems which exclusively operate with license plate recognition are also used. The ascertainment of the registration number, however, can under certain circumstances be subject to errors which are caused, for example, by the incorrect recognition of individual characters of very similar registration numbers. For this reason, the use of additional systems with which motor vehicles can be identified using further features is sensible. Such a system can be based, for example, on contour recognition, in which the match between a currently produced image and an already existing image of a motor vehicle is checked, and identification occurs on the basis of the greatest similarity.
In patent specification EP 1 997 090 B1, a camera positioned next to the road is used to ascertain the three-dimensional shape of a moving vehicle from a plurality of subsequent recordings. Using the ascertained shape, the vehicle type is then identified by way of a comparison with shapes from an already established database. A disadvantage here is that a plurality of recordings are necessary to ascertain the vehicle type, and that the recordings must be taken in correspondence with the position in which the comparison images in the database were produced.
A further variant of the capture and the identification of features of a vehicle is disclosed in EP 2 320 384 A1. Here, one or more characteristic features of the vehicle are ascertained, likewise in the image of a vehicle recorded by a camera. These characteristic features are captured using methods, which are not described in more detail, for image processing in order to ascertain light/dark regions or to calculate contrast, brightness or color value digit sums. Using these features, an already existing, categorized reference image from a database is then ascertained by similarity evaluation. With sufficient correspondence, the recorded vehicle is categorized in accordance with the classified reference image. However, it is conceded that inaccuracies in the sensor technology under different illumination conditions can lead to errors in the evaluation using a single recording, and it is therefore sensible to carry out the assessment using a plurality of images or with the additional use of further sensors. It must therefore be assumed that the capture of the selected characteristic features is significantly dependent on weather influences, light influences and deviating angle ratios of the image recording, and thus a combination of a plurality of image sensors is always necessary to uniquely identify a vehicle.